class_docstr: An example for training/inference.
class_docstr_tok: ["An","example","for","training\/inference","."]
docstr: Make a copy of the current example with utterance features and non categorical features.
docstr_tok: ["Make","a","copy","of","the","current","example","with","utterance","features","and","non","categorical","features","."]
code: def make_copy_of_non_categorical_features(self):
      """Make a copy of the current example with utterance features and non categorical features."""
      new_example = self.make_copy()
      new_example.noncategorical_slot_id = self.noncategorical_slot_id
      new_example.noncategorical_slot_status = (
          self.noncategorical_slot_status
      )
      new_example.utterance_ids = list(self.utterance_ids)
      new_example.utterance_segment = list(self.utterance_segment)
      new_example.utterance_mask = list(self.utterance_mask)
      new_example.start_char_idx = list(self.start_char_idx)
      new_example.end_char_idx = list(self.end_char_idx)
      new_example.user_utterance = self.user_utterance
      new_example.system_utterance = self.system_utterance
      new_example.noncategorical_slot_status = (
          self.noncategorical_slot_status
      )
      new_example.noncategorical_slot_value_start = (
          self.noncategorical_slot_value_start
      )
      new_example.noncategorical_slot_value_end = (
          self.noncategorical_slot_value_end
      )
      return new_example
  
file_path: NeMo/nemo/collections/nlp/data/dialogue/input_example/sgd_input_example.py
imports: from typing import List
  from nemo.collections.nlp.data.dialogue.input_example.input_example import DialogueInputExample
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling the SGDInputExample obj's underlying member method code with example usage: obj.make_copy_of_non_categorical_features() and returns: new_example